We describe a framework for learning an object classifier from a single example. This goal is achieved by emphasizing the relevant dimensions for classification using available ex...
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
In this paper, we adress the question of decoding cognitive information from functional Magnetic Resonance (MR) images using classification techniques. The main bottleneck for acc...
In this paper we present the results of a comparative study of linear and kernel-based methods for face recognition. The methods used for dimensionality reduction are Principal Co...
Himaanshu Gupta, Amit K. Agrawal, Tarun Pruthi, Ch...
We present a novel expert-model of Query-Driven Locally Adaptive (QDLA) Fisher faces for robust face recognition. For each query face, the proposed method first fits local Fisher ...
Yun Fu, Junsong Yuan, Zhu Li, Thomas S. Huang, Yin...